ArticleBiomedical optics express2015
Extended output phasor representation of multi-spectral fluorescence lifetime imaging microscopy.
Article in Biomedical optics express, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning.Journal of biomedical optics · 2022Article
- Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach.PloS one · 2021Article
- Detection of pancreatic tumor cell nuclei via a hyperspectral analysis of pathological slides based on stain spectra.Biomedical optics express · 2019Article
- Phasor plotting with frequency-domain flow cytometry.Optics express · 2016Article
- Deconvolution of fluorescence lifetime imaging microscopy by a library of exponentials.Optics express · 2015Article
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Authors and funding
4 authors.
Funding
Abstract
In this paper, we investigate novel low-dimensional and model-free representations for multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) data. We depart from the classical definition of the phasor in the complex plane to propose the extended output phasor (EOP) and extended phasor (EP) for multi-spectral information. The frequency domain properties of the EOP and EP are analytically studied based on a multiexponential model for the impulse response of the imaged tissue. For practical implementations, the EOP is more appealing since there is no need to perform deconvolution of the instrument response from the measured m-FLIM data, as in the case of EP. Our synthetic and experimental evaluations with m-FLIM datasets of human coronary atherosclerotic plaques show that low frequency indexes have to be employed for a distinctive representation of the EOP and EP, and to reduce noise distortion. The tissue classification of the m-FLIM datasets by EOP and EP also improves with low frequency indexes, and does not present significant differences by using either phasor.
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